Near-Optimal Approximate Duplicate-Detection in Data Streams Over Sliding Windows for the Uniform Query Frequency or Membership Likelihood

2014 ◽  
Author(s):  
Xiujun Wang ◽  
Xiao Zheng ◽  
Zhe Dang ◽  
Xuangou Wu ◽  
Baohua Zhao
Keyword(s):  
Data Streams ◽  
Sliding Windows ◽  
Duplicate Detection

scholarly journals CVS: Fast cardinality estimation for large-scale data streams over sliding windows

2016 ◽  
Vol 194 ◽  
pp. 107-116 ◽  
Author(s):  
Jingsong Shan ◽  
Jianxin Luo ◽  
Guiqiang Ni ◽  
Zhaofeng Wu ◽  
Weiwei Duan
Keyword(s):  
Data Streams ◽  
Large Scale ◽  
Sliding Windows ◽  
Cardinality Estimation ◽  
Large Scale Data ◽  
Scale Data

Dynamic Adjustment of Sliding Windows over Data Streams

2004 ◽  
pp. 24-33 ◽  
Author(s):  
Dongdong Zhang ◽  
Jianzhong Li ◽  
Zhaogong Zhang ◽  
Weiping Wang ◽  
Longjiang Guo
Keyword(s):  
Data Streams ◽  
Dynamic Adjustment ◽  
Sliding Windows

Survey on Data Streams Clustering Techniques

2014 ◽  
Vol 933 ◽  
pp. 768-773 ◽  
Author(s):  
Wei Hua Ma
Keyword(s):  
Big Data ◽  
Data Streams ◽  
Data Stream ◽  
Research Topic ◽  
Sliding Windows ◽  
Clustering Techniques ◽  
Research Results ◽  
Stream Clustering ◽  
Data Stream Clustering

Data stream in a popular research topic in big data era. There are many research results on data stream clustering domain. This paper firstly has a brief introduction to data stream methodologies, such as sampling, sliding windows, etc. Finally, it presents a survey on data streams clustering techniques.

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